Evidence map›Paper›PMID 39812980›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Quantitative Lipidomics of Biological Samples Using Supercritical Fluid Chromatography Mass Spectrometry.

Hiroaki Takeda, Yoshihiro Izumi, Takeshi Bamba

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hiroaki TakedaDepartment of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, Tokyo, Japan.
Yoshihiro IzumiDivision of Metabolomics, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan.
Takeshi BambaDivision of Metabolomics, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan. bamba@bioreg.kyushu-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lipidomics has attracted attention in the discovery of unknown biomolecules and for capturing the changes in metabolism caused by genetic and environmental factors in an unbiased manner. However, obtaining reliable lipidomics data, including structural diversity and quantification data, is still challenging. Supercritical fluid chromatography (SFC) is a suitable technique for separating lipid molecules with high throughput and separation efficiency. Here, we describe a quantitative lipidomics method using SFC coupled with mass spectrometry. This technique is suitable for characterizing the structural diversity of lipids (e.g., phospholipids, sphingolipids, glycolipids, and glycerolipids) with high quantitative accuracy to understand their biological functions.

Indexed as

Chromatography, Supercritical FluidLipidomicsLipidsMass SpectrometryAnimalsHumansLipidsCellsExtracellular vesiclesGlycerolipidsGlycolipidsLipidomicsLipoproteinsLiquid-liquid extractionMass spectrometryOrgansPhospholipidsPlasmaQuantitative analysisSphingolipidsSupercritical fluid chromatographyTissues

Identifiers

PMID39812980

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.